Changelog

Changelog#

0.8.0#

New features#

  • add leaky integrate-and-fire neurons (#564, @jnsbck), Izhikevich neurons, and rate-based neurons (#601, @michaeldeistler)

Minor updates#

  • make delta and v_th in IonotropicSynapse trainable parameters (#599, @jnsbck)

  • make random postsnaptic compartment selection optional in connectivity functions (#489, @kyralianaka)

Bug fixes#

  • Fix bug for groups when .set_ncomp was run (#587, @michaeldeistler)

  • allow .distance to be jitted (#603, @michaeldeistler)

0.7.0#

New Features#

  • Allow ion diffusion with cell.diffuse() and add tutorials (#438, @michaeldeistler):

from jaxley.channels import CaNernstReversal
from jaxley.pumps import CaFaradayConcentrationChange

cell.insert(CaFaradayConcentrationChange())
cell.insert(CaNernstReversal())
cell.diffuse("CaCon_i")
cell.set("axial_diffusion_CaCon_i", 1.0)

  • Introduce ion pumps (#438, @michaeldeistler)

Bug fixes#

  • Fix for simulation of morphologies with inhomogenous numbers of compartments (#438, @michaeldeistler)

  • Bugfix for types assigned by SWC reader when soma is traced by a single point (#582, @Kartik-Sama, @michaeldeistler).

Code health#

  • add new release workflow (#588, @jnsbck)

  • update FAQ and tutorials (#593, @michaeldeistler)

  • make random post compartment selection optional in connectivity functions (#489 @kyralianaka)

0.6.2#

  • also remove nseg from tutorials (#580, @jnsbck)

0.6.1#

  • Fixup for failing readthedocs build of v0.6.0 (#579, @michaeldeistler)

  • Deprecate nseg in favor of ncomp.

0.6.0#

Pin of JAX version#

Installing Jaxley will no longer install the newest version of JAX. We realized that, on CPU, with version jax==0.4.32 or newer, simulation time in Jaxley is 10x slower and gradient time is 5x slower as compared to older versions of JAX. Newer versions of JAX can be made equally fast as older versions by setting os.environ['XLA_FLAGS'] = '--xla_cpu_use_thunk_runtime=false' at the beginning of your jupyter notebook (#570, @michaeldeistler).

New Features#

  • Add ability to record synaptic currents (#523, @ntolley). Recordings can be turned on with

net.record("i_IonotropicSynapse")

  • refactor plotting (#539, @jnsbck).

    • rm networkx dependency

    • add Network.arrange_in_layers

    • disentangle moving of cells and plotting in Network.vis. To get the same as net.vis(layers=[3,3]), one now has to do:

net.arrange_in_layers([3,3])
net.vis()

  • Allow parameter sharing for groups of different sizes, i.e. due to inhomogenous numbers of compartments or for synapses with the same (pre-)synaptic parameters but different numbers of post-synaptic partners. (#514, @jnsbck)

  • Add jaxley.io.graph for exporting and importing of jaxley modules to and from networkx graph objects (#355, @jnsbck).

    • Adds a new (and improved) SWC reader, which is more flexible and should also be easier to extend in the future.

    from jaxley.io.graph import swc_to_graph, from_graph
graph = swc_to_graph(fname)
# do something to the swc graph, i.e. prune it
pruned_graph = do_something_to_graph(graph)
cell = from_graph(pruned_graph, ncomp=4)

    • Adds a new to_graph method for jaxley modules, which exports a module to a networkX graph. This allows to seamlessly work with networkX’s graph manipulation or visualization functions.

    • "graph" can now also be selected as a backend in the read_swc.

    • See the improved SWC reader tutorial for more details.

Code Health#

  • changelog added to CI (#537, #558, @jnsbck)

  • Add regression tests and supporting workflows for maintaining baselines (#475, #546, @jnsbck).

    • Regression tests can be triggered by commenting “/test_regression” on a PR.

    • Regression tests can be done locally by running NEW_BASELINE=1 pytest -m regression i.e. on main and then pytest -m regression on feature, which will produce a test report (printed to the console and saved to .txt).

  • Allow inspecting the version via import jaxley as jx; print(jx.__version__) (#577, @michaeldeistler).

Bug fixes#

  • Fixed inconsistency with type assertions arising due to numpy functions returning different dtypes on platforms like Windows (#567, @Kartik-Sama)

0.5.0#

API changes#

  • Synapse views no longer exist (#447, #453, @jnsbck). Previous code such as

net.IonotropicSynapse.set("IonotropicSynapse_s", 0.2)

must be updated to:

net.set("IonotropicSynapse_s", 0.2)

For a more detailed tutorial on how to index synapses, see this new tutorial.

  • Throughout the codebase, we renamed any occurance of seg (for segment) to comp (for compartment). The most notable user-facing changes are:

    • branch = jx.Branch(comp, ncomp=4)

    • cell = jx.read_swc(fname, ncomp=4)

  • New defaults for the SWC reader with jx.read_swc(). By default, we now have assign_groups=True (previously False) and max_branch_len=None (previously 300.0).

  • We renamed .view to .nodes, e.g., cell.branch(0).nodes (#447, #453, @jnsbck).

  • We renamed _update_nodes_with_xyz() to compute_compartment_centers() (#520, @jnsbck)

  • We updated the way in which transformations are built (#455, @manuelgloeckler). Previous code such as

tf = jx.ParamTransform(
    lower={"radius": 0.1, "length": 2.0},
    lower={"radius": 3.0, "length": 20.0},
)

must be updated to:

from jaxley.optimize.transforms import ParamTransform, SigmoidTransform
transforms = [
    {"radius": SigmoidTransform(lower=0.1, upper=3.0)},
    {"length": SigmoidTransform(lower=2.0, upper=20.0)},
]
tf = jt.ParamTransform(transforms)

New features#

  • Added a new delete_channel() method (#521, @jnsbck)

  • Allow to write trainables to the module (#470, @michaeldeistler):

net.make_trainable("radius")
params = net.get_parameters()
net.write_trainables(params)

  • Expose the step function to allow for fine-grained simulation (#466, @manuelgloeckler)

  • More flexible and throrough viewing (#447, #453, @jnsbck)

  • Boolean indexing for cells, branches, and comps (@494, @jnsbck):

r_greater_1 = net.nodes.groupby("global_cell_index")["radius"].mean() > 1
net[r_greater_1].nodes.vis()

  • check if recordings are empty (#460, @deezer257)

  • enable clamp to be jitted and vmapped with data_clamp() (#374, @kyralianaka)

Bug fixes#

  • allow for cells that were read from swc to be pickled (#525, @jnsbck)

  • fix units of compute_current() in channels (#461, @michaeldeistler)

  • fix issues with plotting when the morphology has a different number of compartments (#513, @jnsbck)

Documentation#

  • new tutorial on synapse indexing (#464, @michaeldeistler, @zinaStef)

  • new tutorial on parameter sharing (#464, @michaeldeistler, @zinaStef)

  • new tutorial on modules and views (#493, @jnsbck)

  • improved tutorial on building channel models (#473, @simoneeb)

  • get rid of tensorflow dependency by defining our simple dataloader in the tutorial (#484, @jnsbck)

  • new FAQ about rate-based networks (#531, @michaeldeistler)

Code health#

  • refactor tests with fixtures (@479, #499, @fabioseel, @jnsbck)

  • make several attributes private (#495, @ntolley)

  • move read_swc.py to new io folder (#524, @jnsbck)

  • faster testing for SWC and plotting (#479, @fabioseel)

  • automated tests to check if tutorials can be run (#480, @jnsbck)

  • add helpers to deprecate functions and kwargs (#516, @jnsbck)

0.4.0#

New features#

  • Changing the number of compartments: cell.branch(0).set_ncomp(4) (#436, #440, #445, @michaeldeistler, @jnsbck)

  • New options for plotting: cell.vis(type='comp') and cell.vis(type='morph') (#432, #437, @jnsbck)

  • Speed optimization for jx.integrate(..., voltage_solver="jaxley.stone") (#442, @michaeldeistler)

Documentation#

v0.3.0#

New features#

  • New solver: jx.integrate(..., voltage_solver="jax.sparse") which has very low compile time (#418, @michaeldeistler)

  • Support for different number of compartments per branch at initilization (modifying the number of compartments after initialization is not yet supported, #418, #426, @michaeldeistler)

Bugfixes#

  • Bugfix for capacitances and their interplay with axial conductances (Thanks @Tunenip, #426, @michaeldeistler)

  • Bugfixes for tutorials on website

v0.2.1#

  • Bugfix for using states in init_state of the channel (#421, @michaeldeistler)

  • Bugfix for tutorial on building custom channels (#421, @michaeldeistler)

  • Add jaxley-mech as dev dependency to use it in testsing (#421, @michaeldeistler)

v0.2.0#

New features#

  • Cranck-Nicolson solver (#413, @michaeldeistler)

  • Forward Euler solver for compartments and branches (#413, @michaeldeistler)

  • Add option to access states in channel.init_state (#416, @michaeldeistler)

Bugfixes#

  • Bugfix for interpolation of x, y, z values (#411, @jnsbck)

v0.1.2#

  • Minor fixups for README, website, and PyPI landing page

v0.1.1#

  • Minor fixups for README, website, and PyPI landing page

v0.1.0#

  • First public version

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